The New Digitized World
Machine Learning and Artificial Intelligence are becoming more and more important for intelligence professionals and analysts. The simple reason for that is that we are living in a sociological era unlike anything in history. New technology has literally changed sociological and behavior patterns in humans. Our communication, interaction, social engagement and networks have all been revolutionized through the development of a digitized world.
This digitized technology adoption is literally borderless. This results in a globalization of a digitized society on an unprecedented scale. New ideas and applications are traveling at the speed of the internet. Multi-billion dollar “game changing” companies rise and fall based on the newest technological disruption that is almost becoming a monthly “expectation”, rather than a generational revolutionary development.
One underlying factor to succeed in this new environment, which is universal and absolute is : Time – this is the differentiator, no matter what industry you’re in. It isn’t just about these companies being able to execute a good idea. It’s also about the inability of the established fixtures in the industry to act quickly to transform its own business models to compete. Their inability to compete is usually based on either 1) not seeing the transition towards digitization, 2) seeing and ignoring by not wanting to get out of their “comfort zone”, or 3) seeing, responding, but not fully understanding the implications and requirements, and thus missing that key factor we previously mentioned – Time to Execution.
In today’s world, every company is at risk of missing a market opportunity, not securing their enterprise and being disrupted by a new idea or business model.
Time to Insights and Time to Execution are factors that are now more critical than ever, as the ability to respond to market disruptions is quickly evolving, from months and years to days and weeks.
This was part one in our new blog series, based on the article “Machine Learning Implications for Intelligence and Insights”, written by Jesper Martell , Comintelli, and Paul Santilli, Hewlett Packard Enterprise.